Instructor embedding huggingface download hkunlp. multi-train Update README.

Instructor embedding huggingface download hkunlp param encode_kwargs: Dict [str, Any] [Optional] ¶ Keyword arguments to pass when calling the encode method of the model. text-semantic Thanks a lot for your interest in the INSTRUCTOR model! We provide a few Hi, Thanks a lot for your interest in the INSTRUCTOR model! You may need to move both models and encoding texts to the GPU. quantize_dynamic (model, {torch. When I load the local trained model I got this: This IS expected if you are initializing T5EncoderModel from the checkpoint of a model trained on another task or with another architecture (e. quantization. embeddings = HuggingFaceInstructEmbeddings() param model_name: str = 'hkunlp/instructor-large' ¶ Model name to use. 33. like Sentence Similarity PyTorch Sentence Transformers Transformers English t5 text-embedding embeddings information-retrieval beir text-classification language-model text-clustering text instruction and the merge to the input. This repo contains an API for instructor-xl embedding model deployed on huggingface: https://huggingface. I am doing conversation retrieval and the process got stuck on load INSTRUCTOR_Transformer, max_seq_length 512 and no hkunlp / instructor-xl. Sentence Similarity • Updated I am trying to deploy the instructor embedding using the following: from typing import Any, List from InstructorEmbedding import INSTRUCTOR. With instructions, the embeddings are **domain-specific** (e. sentence what is the maximum text limit that could be embedded successfully without truncation 2023. nodes import EmbeddingRetriever from ha hkunlp / instructor-large. Feel free to add any questions or comments! display benchmark metrics for base sized model. Sentence Similarity sentence-transformers PyTorch Transformers English t5 text-embedding embeddings information-retrieval beir text-classification language-model text-clustering text-semantic-similarity text instructor-large / spiece. like 544. One of the instruct embedding models is used in the HuggingFaceInstructEmbeddings class. json. _load_sbert_model() 3 #23 opened 5 months ago by Nedala10. How can I instruct to use GPU instead of using my CPU for embedding ? See translation. like 495. tqdm(np. We introduce INSTRUCTOR, a new method for computing text embeddings given task instructions: every text input is embedded together with instructions explaining the use case (e. Here's how I import it and verify that it's working: from InstructorEmbedding import INSTRUCTOR model = INSTRUCTOR('hkunlp/ the config JSON for pooling includes arguments that are not valid for the Pooling function. #24 opened 7 months ago by ishucs. _load_sbert_model() 3 #23 opened 8 months ago by Nedala10. Instrucor-Large has 95k downloads, so I assumed this was the model you were referring. preview code | raw Copy download link. ) to a fixed-length vector in test time **without further training**. Sentence Similarity • Updated Apr 21, 2023 • 279k • 495 hkunlp/instructor-base. text-clustering. ) by I was wondering if I should use for my document Q&A Chatbot Embeddings or Instructor Embeddings from HuggingFace with LangChain. 1 embedding processing happens locally on my system or on hugging face server #26 opened 9 months ago by sushmitaraj19365. json: 100%|#####| 2. One Embedder, Any Task: Instruction-Finetuned Text Embeddings. Hi, you may see the network class here: https://huggingface. Feel free to add further questions or comments! Edit Preview Active filters: text-embedding. ) ***by simply providing the task instruction, without any finetuning***. like 480. Reload to refresh your session. ) ***by simply providing the hkunlp/instructor-base We introduce Instructor👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. In case of code what worked out better is parsing it with tree-sitter, then indexing the resulting code constructs in a meaningful way. py at main · xlang-ai/instructor-embedding After much more digging around, I realized there were several things going quite wrong in the above implementation. You may need to take care of the model/data copy/parallel issues in the encoding. history blame contribute delete Safe. Are Instructor embeddings normalized by default? I see a normalize_embeddings boolean parameter in the encode API. ) by We introduce Instructor👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. array_split's second argument takes the desired number of splits as input, not the desired split size for chunk in tqdm. , classification, retrieval, clustering, text evaluation, etc. param model_name: str = 'hkunlp/instructor-large' ¶ Model name to use. I get a TypeError: init() got an unexpected keyword argument 'pooling_mode_weightedmean_tokens' When trying to load the model using sentence transformers in a Google Colab Pro notebook. txt for inference endpoint and handler that allows use of langchain. , instructor_model_name: str = "hkunlp/instructor-large", instruction: str = "Represent a document for question answer retrieval:", **kwargs: Any, ) -> None: self. These instructions provide contextual information specific to a given task or domain, which allows the model to generate embeddings more suitable for specific downstream tasks. 0b2f225 almost 2 years ago. like Do I need to strip all that before embedding, or does it help to understand the meaning of the text? multi-train May 10. history blame contribute delete No virus 792 kB. Ask Question I want to solve this by make instructor-xl as service using compute engine. 2. instructor-base / spiece. So I just downloaded the model and ran it from langchain. ) This is a fork for the Instructor model becuase the original repository isn't kept up anymore. , science, finance, etc. I am not sure if the e5 model (first on the MTEB leaderboard) would work well with your data. like 372. Unlike encoders from prior work that are more specialized, INSTRUCTOR is a single embedder that can generate text embeddings tailored to different Sentence Similarity Sentence Transformers PyTorch Transformers English t5 text-embedding embeddings information-retrieval beir text-classification language-model text-clustering text-semantic-similarity text-evaluation prompt-retrieval text-reranking feature-extraction English Sentence Similarity natural_questions ms_marco fever hotpot_qa mteb Eval Results text We’re on a journey to advance and democratize artificial intelligence through open source and open science. Got stuck on load INSTRUCTOR_Transformer. Embedding dimension? 1 #11 opened about 1 month ago by jmt415. Instructor👨‍ achieves sota on 70 diverse embedding hkunlp/instructor-large We introduce Instructor👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. finding related documents for a given sentence). co/hkunlp/instructor-xl We introduce Instructor👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. It is too big to display, but We introduce **Instructor**👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. NLP Group of The University of Hong Kong 75. """ documents = ["foo bar"] model_name = Have you tried the Instructor-XL Embedding Model? Its currently in the second place on the MTEB leaderboard. The following are in the config (not in this order): To utilize the HuggingFaceEmbeddings class for text embedding, you first need to install the necessary package. like 223. 3 We’re on a journey to advance and democratize artificial intelligence through open source and open science. 768. Here’s a simple example: We introduce INSTRUCTOR, a new method for computing text embeddings given task instructions: every text input is embedded together with instructions explaining the use case (e. [ACL 2023] One Embedder, Any Task: Instruction-Finetuned Text Embeddings - instructor-embedding/train. Sentence Similarity • Updated Apr 30 • 17. param model_kwargs: Dict [str, Any] [Optional] # Keyword arguments to pass to the model. Feel free to add any further questions or comments! There's now native support, with show_progress_bar argument. embed_documents (texts: List [str]) → List [List [float]] [source] ¶ Compute doc embeddings using a HuggingFace instruct model. What follows is the original repository's readme file. is INSTRUCTOR embeddings compatible with LLAMA2? 1 hkunlp/instructor-base We introduce Instructor👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. f3c4dc8 about 1 year ago. ) Get TypeError: Pooling. then do the below: from sentence_transformers import SentenceTransformer, models (modules=[word_embedding_model, pooling_model]) You can check whether the model is correctly loaded or not by doing the below: Text embedding tool. Hi, Thanks a lot for your interest in the INSTRUCTOR! It is possible to run the XL model on GPU devices. model. with st. vectorstores import FAISS. 1 #17 opened 10 months ago by hiranya911. Lambda-Instructor is an experimental deployment of the text-embedding model Instructor-Large on AWS Lambda. I have millions of data with lengths ranging from 10 to 1000 tokens (using the instructor-large tokenizer). But with or without this parameter, encode seems to produce the same result, and it does indeed looks normalized. co/hkunlp Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers; Advertising & Talent Reach devs & technologists worldwide about your product, service or employer brand; OverflowAI GenAI features for Teams; OverflowAPI Train & fine-tune LLMs; Labs The future of collective knowledge sharing; About the company The default input length for instructor-xl is 512. NLP Group of The University of Hong Kong org Apr 9, 2023. Sentence Similarity • Updated Jan 21, 2023 • 22k • 545 hkunlp/instructor-base. This loader interfaces with the Hugging Face Models API to fetch and load model metadata and README files. sidebar: st. ) This repository contains the code and pre-trained models for our paper One Embedder, Any Ta We introduce Instructor👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. hkunlp/instructor-large We introduce Instructor👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. Citation Downloads last month 100,974 Safetensors. raw Copy download link. title('LLM Chat App') st. . For information on accessing the model, you can click on the “Use in Library” We introduce Instructor 👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. LangChain is an open-source framework that makes building applications with Large Language Models (LLMs) easy. Instruction to use for embedding documents. NLP Group of The University of Hong Kong org Sep 26, 2023. No sentence-transformers model found with name hkunlp/instructor-large. Load model information from Hugging Face Hub, including README content. Image by Author Langchain. All functionality related to the Hugging Face Platform. Clear all . Others have tried with 24GB memory. embeddings. markdown(''' ## About This app is an LLM-powered chatbot built using: - Streamlit - Langchain - HuggingFace instructor-base like 95 Sentence Similarity Sentence Transformers PyTorch Transformers English t5 text-embedding embeddings information-retrieval beir text-classification language-model text-clustering text-semantic-similarity text-evaluation prompt-retrieval text-reranking feature-extraction English Sentence Similarity natural_questions ms_marco fever instructor-xl like 487 Sentence Similarity sentence-transformers PyTorch Transformers English t5 text-embedding embeddings information-retrieval beir text-classification language-model text-clustering text-semantic-similarity text-evaluation prompt-retrieval text-reranking feature-extraction English Sentence Similarity natural_questions ms_marco fever Hello, I had a previous project where I was running a function with the instructor similarity to calculate the semantic similarity, I come back to this project finding that I am unable to load the Instruction to use for embedding documents. 0 can be used to create embeddings using the INSTRUCTOR Embedding Models. is INSTRUCTOR embeddings compatible with LLAMA2? 1 hkunlp / instructor-xl. clone of hkunlp/instructor with added requirements. language-model. like 540. multi-train Update README. So, when I perform custom vectorization on my dataset, a significant portion of GPU memory is actually wasted. t5. but I'm not sure how to use/call the embedding. model = INSTRUCTOR() model_path = ". hkunlp / instructor-xl. + This is a general embedding model: It maps **any** piece of text (e. Instructor👨‍ achieves sota on 70 diverse embedding tasks! hkunlp/instructor-large. We introduce Instructor👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. English. 1 #17 opened about 1 year ago by hiranya911. This only happens with the XL model, large and smaller seem to work fine. You don't need embedding for that, only an SQL server or some classic full text search indexing solution. Apr 9, 2023. Hi, Thanks a lot for your interest in the INSTRUCTOR model! For the html descriptions, I would suggest removing the tags for better semantic understanding. INSTRUCTOR is an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. embeddings import HuggingFaceInstructEmbeddings from InstructorEmbedding import INSTRUCTOR from langchain. Hi, Thanks for your interest in the INSTRUCTOR model! One good way to run the INSTRUCTOR model of course, here you go: hkunlp (NLP Group of The University of Hong Kong) (huggingface. NLP Group of The University sentence-transformers. Sentence Is anyone running an API for embedding? Otherwise what is the best host for a serverless api to do embeddings? Thanks. 4 Huggingface Instructor Embeddings using URL or Service. 2 kB Instruction to use for embedding documents. ) and domains (e. Upload images, audio, and videos by dragging in the text input, pasting, or clicking here. Follow. Sentence Sentence Similarity Sentence Transformers PyTorch Transformers English t5 text-embedding embeddings information-retrieval beir text-classification language-model text-clustering text-semantic-similarity text-evaluation prompt-retrieval text-reranking feature-extraction English Sentence Similarity natural We’re on a journey to advance and democratize artificial intelligence through open source and open science. text-semantic-similarity. As you will see, the beloved and almost champion in the embedding-retrieval hkunlp/instructor-large will have a very different approach, but once you understand the logic behind it, you can We’re on a journey to advance and democratize artificial intelligence through open source and open science. Please refer to our project page for a quick project overview. Normalizing embedding vectors. As of June-2023, it seems to be on a level with OpenAI's from langchain_community. I want to download model before hand and then load it locally by providing path. In case it helps anyone in the future, a non-exhaustive list follows: Thanks for sharing this model with the community. , classification, retrieval, clustering, text We’re on a journey to advance and democratize artificial intelligence through open source and open science. Hi, Thanks a lot for your interest in the INSTRUCTOR model! The embedding dimension for the model is 768. , a title, a sentence, a document, etc. The API allows you to search and filter models based on specific criteria such as model tags, authors, and more. Hi, Thanks a lot for your interest in the INSTRUCTOR model! The dimension for sentence embedding is 768. model_name = "hkunlp/instructor-large" embed_instruction = "Represent the text from the Hugging Face code documentation" query_instruction = "Query the most relevant text from the Hugging Face code documentation" embedding = HuggingFaceInstructEmbeddings(model_name=model_name, WARN: You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference hkunlp / instructor-xl. e2eb52c over 1 year ago. param query_instruction: str = 'Represent the question for retrieving supporting documents: ' ¶ Instruction to use for embedding query. ) by simply providing the We’re on a journey to advance and democratize artificial intelligence through open source and open science. 1B params, which seems much more comparable to the 111M sized-models than instrucutor-large with 335M params. like 102. ) and **task-aware** (e. cuda. apiVersion: apps/v1 kind: Deployment metadata: name: instructor-xl-tei names Got the training working by fintuning instructor-large. Hi, Thanks a lot for your interest in the INSTRUCTOR model! By default, the maximum input length is 512, but it should be compatible with documents that have sequence length 1024. information-retrieval. multi-train Upload 9 files. hkunlp/instructor-xl Sentence Similarity • Updated Jan 21, 2023 • 20. like 483. This can be done using the following command: %pip install -qU langchain-huggingface Once the package is installed, you can import the HuggingFaceEmbeddings class and create an instance of it. in your paper you write that instructor-base has 0. Feel free to add any further questions or comments! See translation. I'm trying to assess what could be a good starting training set size, loss temperature and what could be a good k of negative pairs per Returns: FAISS: Vector store """ # Automatically choose device: CUDA if available, otherwise CPU device = 'cuda' if torch. multi-train. Sentence Similarity • Updated hkunlp / instructor-xl. like 546. beir. We introduce Instructor👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. Transformers. I've also made some improvements to their source code: Fixing it to work with the sentence-transformers library above 2. Here are all the details: Upload images, audio, and videos by dragging in the text input, pasting, or clicking here. Sentence Similarity • Updated Apr 21 • 182k • 364 hkunlp/instructor-base. nn. #24 opened 4 months ago by ishucs. Sentence Similarity • Updated Apr 21, 2023 • 185k • 489 hkunlp/instructor-xl. PyTorch. Ability to specify where you want the model donwloaded with the "cache_dir" parameter. Same as hkunlp/instructor-large, except using a custom handler so it can be deployed with HF Inference Endpoints hkunlp/instructor-large We introduce Instructor👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. hkunlp/instructor-xl · embedding processing happens locally on my system or hi , when i use this command - instructor_embeddings = HuggingFaceInstructEmbeddings hkunlp/instructor-xl We introduce Instructor👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. embeddings import HuggingFaceInstructEmbeddings, HuggingFaceEmbeddings from langchain. import tqdm document_embeddings = [] # np. 718cedb over 1 year ago. It should only consume reasonable spaces with controlled batch sizes. Instructor👨‍ achieves sota on 70 diverse embedding Upload images, audio, and videos by dragging in the text input, pasting, or clicking here. I couldn’t find this answer online and Bing hallucinated one. 5k • 48 hkunlp/instructor-large. 66. co) Just scroll down a bit to see their models. load(model_path) Encode sentences. Sentence Similarity sentence-transformers PyTorch Transformers English t5 text-embedding embeddings information-retrieval beir text-classification language-model text-clustering text-semantic-similarity text instructor-xl / spiece. Feel free to add further questions or comments! tiagofreitas87. We’re on a journey to advance and democratize artificial intelligence through open source and open science. __init__() got an unexpected keyword argument 'pooling_mode_weightedmean_tokens' when init model We’re on a journey to advance and democratize artificial intelligence through open source and open science. sentence = "3D ActionSLAM: wearable person tracking in multi-floor environments the science title is NASA" hkunlp/instructor-base We introduce Instructor👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. Instructor👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. Load the model. history blame contribute delete while running this code: from InstructorEmbedding import INSTRUCTOR. Hugging Face model loader . ce48b21 almost 2 years ago. I've tried to use instructor-large for code search, but it did not seem to work too well. instructor-large like 449 Sentence Similarity sentence-transformers PyTorch Transformers English t5 text-embedding embeddings information-retrieval beir text-classification language-model text-clustering text-semantic-similarity text-evaluation prompt-retrieval text-reranking feature-extraction English Sentence Similarity natural_questions ms_marco fever We’re on a journey to advance and democratize artificial intelligence through open source and open science. Sentence Similarity • Updated Jan 21 • 22. Instruct Embeddings on Hugging Face. Tensor type. 3k • 553 Jzuluaga/accent-id-commonaccent_xlsr-es-spanish Hello! If I want to create one embedding for a longer document, what is the proposed way to do it? Would it be to embed multiple chunks of 512 tokens and then take the average of the resulting embedding vectors? We’re on a journey to advance and democratize artificial intelligence through open source and open science. Like this: We introduce Instructor 👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. 4. instructor-large / tokenizer_config. sentence-transformers. hkunlp/instructor-xl We introduce Instructor👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. #INSTRUCTOR. Hi all, I'm trying to use this model hkunlp/instructor-large in my retriver to calculate embeddings for my ES index but I get this error- Code- from haystack. 7edca84 over 1 year ago. ) by simply + This is a general embedding model: It maps **any** piece of text (e. Hi, Thanks a lot for your interest in the INSTRUCTOR! The maximum input length is 512. #3 opened over 1 year ago by MoritzLaurer hkunlp / instructor-base. instructor-large. instructor-base like 74 Sentence Similarity Sentence Transformers PyTorch Transformers English t5 text-embedding embeddings information-retrieval beir text-classification language-model text-clustering text-semantic-similarity text-evaluation prompt-retrieval text-reranking feature-extraction English Sentence Similarity natural_questions ms_marco fever hotpot_qa mteb Eval Results text-embedding. moka-ai/m3e-base. md. Instructor-Large is a model built by the NLP Group of The University of Hong Kong under the Apache-2. Sort: Most downloads hkunlp/instructor-large. ) by For text embedding tasks like text retrieval or semantic similarity, what matters is the relative order of the scores instead of the absolute values, so this should not be an issue. Jun Dears , i am trying to use #HuggingFaceInstructEmbeddings We’re on a journey to advance and democratize artificial intelligence through open source and open science. , customized for classification, information retrieval, etc. ) by simply providing the task instruction, without any finetuning. ) by simply providing Trying to deploy the Embedding model "hkunlp/instructor-xl" Below is the Deployment file used with the model-id as args. ) We’re on a journey to advance and democratize artificial intelligence through open source and open science. If a model on the Hub is tied to a supported library, loading the model can be done in just a few lines. However, when analyzing my own dataset (which consists of approximately 10 million entries), I found that the average length of my strings is around 160 tokens. 4k • 84 hkunlp/instructor-xl. How can i do that ? instructor-xl / README. /instructor-xl" # Update this with the correct path model. 0 license and performs well on retrieval tasks (i. The dimension of embedding vectors is [ACL 2023] One Embedder, Any Task: Instruction-Finetuned Text Embeddings - Issues · xlang-ai/instructor-embedding The problem is when I want to call instructor-xl, it's always error: Downloading ()7f436/tokenizer. ) by simply providing the task instruction, without any finetu We introduce INSTRUCTOR, a new method for computing text embeddings given task instructions: every text input is embedded together with instructions explaining the use Properly download the models from huggingface using the new "snapshot download" API. Instructor👨‍ achieves sota on 70 diverse embedding tasks! hkunlp / instructor-large. like 553. We introduce Instructor👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings We’re on a journey to advance and democratize artificial intelligence through open source and open science. download history blame contribute This custom component for Haystack 2. , task and domain descriptions). Sentence Similarity • I'm investigating what would take to further fine tune Instructor-XL to a legal domain for retrival tasks. 4M params. Properly download the models from huggingface using the new "snapshot download" API. Sentence which has come out in the form of embedding, to this model and have it provide me with a task-specific embedding for various tasks. This file is stored with Git LFS. like 530. I'm using instructor-xl for embedding inference and have encountered some issues. download history blame contribute delete No virus To Quantize the Instructor embedding model, run the following code: # imports import torch from InstructorEmbedding import INSTRUCTOR # load the model model = INSTRUCTOR ('hkunlp/instructor-large', device = 'cpu') # you can use GPU # quantize the model qmodel = torch. text-classification. pevogam. Otherwise you can always use tqdm very easily yourself:. We introduce Instructor👨‍🏫, an instruction-finetuned text embedding model that can You signed in with another tab or window. Feel free to add any [ACL 2023] One Embedder, Any Task: Instruction-Finetuned Text Embeddings - kurhula/xlang-ai_instructor-embedding Now, INSTRUCTOR embeddings are a type of text embedding, but they incorporate additional task-specific instructions into the embedding process. The Instructor-XL paper mentions that they trained it on retrieving data with code (CodeSearchNet). do html documents need tags removed? 1 #10 opened about 1 month ago by awokeknowing. history blame pipeline_tag: what are the LLM compatible with INSTRUCTOR Embeddings are there any git links with sample code. Model size (and ensuing memory requirements) and embedding speed is quite important for large corpora and directly comparable metrics of roughly 111M sized-models would be great. As the INSTRUCTOR model is only trained on English texts, it may not support Download all the files from huggingface save them in a folder locally. is_available() else 'cpu' # Initialize HuggingFaceInstructEmbeddings with the chosen device embeddings = HuggingFaceInstructEmbeddings( query_instruction="Represent the query for retrieval: ", You signed in with another tab or window. See translation. multi-train Upload 10 files. param model_name: str = 'hkunlp/instructor-large' # Model name to use. array_split(documents, len (documents) // 512)): Hi, Thanks a lot for your interest in the INSTRUCTOR model! Yes, it is possible to use INSTRUCTOR in multi-threading process. _model = INSTRUCTOR (instructor We’re on a journey to advance and democratize artificial intelligence through open source and open science. , specialized for science, finance, etc. initializing a BertForSequenceClassification model from a BertForPreTraining model). , task and domain English Speaking Application. text-embedding. Sentence Similarity. e. g. Parameters Sentence Similarity sentence-transformers PyTorch Transformers English t5 text-embedding embeddings information-retrieval beir text-classification language-model text-clustering text-semantic-similarity text-evaluation prompt-retrieval text-reranking feature-extraction English Sentence Similarity natural_questions ms_marco fever hotpot_qa mteb from InstructorEmbedding import INSTRUCTOR # type: ignore from sentence_transformers import SentenceTransformer # Use SentenceTransformer module to use Hugging face Model #import torch. You signed out in another tab or window. hkunlp / instructor-large. NLP Group of The University of Hong Kong 67. For the training/fine-tuning part, I think it would be similar to that of the We’re on a journey to advance and democratize artificial intelligence through open source and open science. This repository contains the code and pre-trained models for our paper One Embedder, Any Task: Instruction-Finetuned Text Embeddings. I'm performing inference on two 3090Ti (24GB each) with a batch size of 128, which just fits the model and data into the GPU memory. I am not sure how to I use embedding model from huggingface vinai/phobert which is trying to download and cache a SentenceTransformer model with the name 'vinai """Test huggingface embeddings. Hugging Face sentence-transformers is a Python framework for state-of-the-art sentence, text and image embeddings. You switched accounts on another tab or window. Hi, Thanks a lot for your interest in the INSTRUCTOR model! You may use the INSTRUCTOR model to embed the texts with the half-precision: from InstructorEmbedding import INSTRUCTOR sentences_a = [['Represent the Science sentence: ','Parton energy loss in QCD matter'], ['Represent the Financial statement: ','The Federal Reserve on Wednesday raised its We’re on a journey to advance and democratize artificial intelligence through open source and open science. Technical Information. Model size. param model_kwargs: Dict [str, Any] [Optional] ¶ Keyword arguments to pass to the model. param encode_kwargs: Dict [str, Any] [Optional] # Keyword arguments to pass when calling the encode method of the model. download Copy download link. ) by Downloading models Integrated libraries. Instructor👨‍ achieves sota on 70 diverse embedding tasks! instructor -base. We introduce **Instructor**👨‍🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e. instructor-base / README.